DGrid's Solution

INFO

DGrid.AI = AI RPC + LLM Reasoning + Distributed Network Nodes

DGrid.AI addresses the critical gaps in Web3 AI and centralized AI limitations through an interconnected ecosystem of nodes, protocols, and decentralized infrastructure.

By integrating standardized AI RPC interfaces, distributed inference nodes, intelligent routing, on-chain settlement, and secure storage, it delivers a trustless, scalable, and user-centric LLM inference network—making AI a native capability of blockchain applications. At its core, DGrid’s solution unifies five foundational components to redefine decentralized AI inference: distributed nodes for model execution, adaptor nodes for coordination, containerized environments for secure reasoning, standardized protocols for universal access, and on-chain mechanisms for transparency.

Together, these elements eliminate reliance on centralized providers, enabling AI to operate as an open, community-governed utility.

DGrid Nodes: Decentralized Inference Execution

DGrid Nodes are community-operated nodes hosting single or multiple LLMs (e.g., Llama-2, Mixtral), forming the network’s computational backbone. These nodes:

• Execute inference tasks for users, processing inputs (e.g., text prompts, smart contract queries) and generating outputs via preloaded models.
• Adapt to hardware capabilities, with operators selecting models matching their server specs (from lightweight 7B-parameter models on basic GPUs to 70B+ models on high-performance hardware).
• Report real-time metrics (latency, Compute Units [CU] consumed) to DGrid Adaptor Nodes, enabling optimal task routing.

By distributing inference across thousands of independent nodes, DGrid eliminates single points of failure and ensures geographic redundancy—critical for Web3 applications requiring 24/7 reliability.

DGrid Adaptor Nodes: Network Coordination & Security

DGrid Adaptor Nodes act as the ecosystem’s "traffic controllers," bridging users, DGrid Nodes, and on-chain systems with three core roles:

• Gateway: Receive user requests via GridRPC, validate parameters (e.g., model availability, pre-payment), and route them to the optimal DGrid Node (based on speed, cost, and historical performance).
• Settlement: Calculate usage bills using CU and latency data, submit transaction details to the Bill Contract for on-chain payment, and archive request logs (inputs, outputs, timestamps) to DStorage.
• Validation: Monitor DGrid Nodes and fellow Adaptor Nodes for service stability (e.g., uptime, result accuracy) and penalize malicious behavior (e.g.,fake outputs, downtime) via staking slashing or node jailing.

This multi-role design ensures the network operates efficiently, securely, and transparently—even with untrusted participants.

GridVM & GridRPC: Trusted Execution & Universal Access

• GridVM: A containerized inference environment that isolates LLM execution on DGrid Nodes, preventing cross-task interference and ensuring model integrity. It generates cryptographic proofs of inference results (e.g., input/output hashes) for validation by Adaptor Nodes, enabling trustless verification without central oversight.
• GridRPC: A standardized JSON-RPC protocol that simplifies user access to the network’s models. It provides a unified API for invoking any LLM (regardless of node or model type) and integrates EIP-712 signatures to authenticate user requests—ensuring only authorized, pre-paid tasks are processed.

Together, GridVM and GridRPC solve Web3 AI’s "trust gap" and "interface fragmentation," making LLM integration as straightforward as calling a smart contract.

Bill Contract & DStorage: On-Chain Transparency

• Bill Contract: A blockchain-deployed smart contract that automates $DGAItoken settlements between users and nodes. It calculates fees based on CU (Compute Units) and latency, deducts payment from users, and distributes rewards to node operators—eliminating intermediaries.
• DStorage: A decentralized storage network that archives all inference request data (via Adaptor Nodes) for auditability. Users can verify billing details, and nodes can prove task completion, enhancing transparency for disputes or compliance.

Security Mechanism

DGrid.AI has established a comprehensive security framework to ensure trustlessness in a decentralized network, combining technical safeguards and on-chain transparency:

Trusted Inference Environments

• Task Isolation: GridVM uses containerization to sandbox each inference task, preventing data leaks or interference between tasks.
• Immutable Runtimes: DGrid Node operators cannot modify LLM weights or execution environments, ensuring consistent model behavior across the network.
• Resource Controls: Strict limits on CPU, GPU, and network usage (enforced by Adaptor Nodes) prevent denial-of-service attacks.

On-Chain Auditing and Accountability

• Immutable Records: All critical activities—node registrations, inference metadata (inputs/outputs), fee settlements, and rewards—are recorded on-chain via the Bill Contract and archived in DStorage.
• Automated Penalties: DGrid Adaptor Nodes monitor node behavior; malicious actors (e.g., submitting fake results) face staked token slashing or jailing, enforced by smart contracts.
• Decentralized Governance: $DGAI token holders vote on protocol upgrades, fee structures, and security parameters, ensuring the network evolves in line with community interests.

By combining secure inference environments, on-chain transparency, and community governance, DGrid.AI ensures the network operates in a secure, reliable, and trustless manner—delivering robust decentralized AI inference services to users.

dToken: Incentives & Governance

$DGAI (dToken) serves as the network’s economic engine, aligning interests across the ecosystem:

• Payments: Users pay $DGAI for inference tasks, with fees dynamically adjusted via the Bill Contract.
• Rewards: Node operators earn $DGAI based on contribution quality (e.g., low latency, high uptime) and validation participation.
• Staking: DGrid Nodes and Adaptor Nodes must stake $DGAI to participate, with slashing for misconduct.
• Governance: Token holders vote on protocol parameters (e.g., fee structures, model whitelisting) to guide network evolution.

This architecture delivers a solution that is scalable (anyone can operate a node),trustless (on-chain proofs replace reliance on intermediaries), and Web3-native (integrated with blockchain workflows). By unifying distributed execution, intelligent coordination, secure reasoning, and transparent settlement, DGrid.AItransforms LLM inference into a foundational capability for Web3—from DeFi strategy analyzers to on-chain chatbots and more.